Time series are data observed over time (either in continuous time or at discrete time periods).

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R GMM - Error in solve.default(x$v, gb) : system is computationally singular: reciprocal condition number

I'm having the following problem estimating something in GMM in R. I have created a "Hello World" below. In principle, I would not need GMM to estimate the parameters, but I want to use it to obtain ...
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1answer
50 views

F test to test equality of variance

I have a single time series which will be divided on the date of the policy change before and after. I want to compare the variances between the two time sections and I am told to do an F test of ...
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2answers
50 views

Forecasting: Different Model for 1 month, 2 month, 6 month forecasts?

I'm still trying to expand my statistics and forecasting technique knowledge. Right now I'm forecasting seasonal contact patterns, so the simplest model I can understand with seasonality is a ...
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22 views

What would be an ideal measure for the synchrony of laughter?

I am exploring the relationship between the quality of connection two people share and the tendency for their laughter to synchronize. In order to do this, I need some way to quantify the degree of ...
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32 views

Transforming time series of different time horizon to stationary

I have a list of monthly time series data with different time periods and different order of integration. I want to transform them all to stationary and a same time period. I noticed that the order ...
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53 views

Multicollinearity with Interaction (high VIF)

When I check the VIF of my independent variables with the dependent variable, it looks normal and less than 5 but when I add the interaction variables, the VIF increase to 48 for some variables. I ...
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35 views

understand forecasts in linear state space models

The Kalman Filter provides the one-step-ahead forecasts within the recursions. We start estimating the (unkown) variance of the parameters for instance through MCMC ...
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48 views

First order autocorrelation of a certain AR process

How could I compute the first order autocorrelation of the process $x_t = \delta + \phi x_{t-1} + \eta_t$? Could anyone give me some pointers? I tried this: $E(\delta + \phi x_{t-1} + \eta_t - ...
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18 views

Hp testing on cointegrating vectors of an identified VECM

I have estimated a VECM model, then I have used linear restrictions to identify and over-identify my model. Now I have the following output. How can I test the significance of the coefficients in the ...
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52 views

what is K in fourier function of R

I am using fourier() function of R which has arguments x,h,K. Can any body please explain me what is 'K' in this function and what is the use of it. Thanks in ...
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2answers
61 views

Prove expression for variance AR(1)

For the AR(1) process $x_t = \delta + \phi x_{t-1} + \eta_t$, I am trying to prove that the variance is: $\sigma_x^2 = \sigma_\eta^2/(1-\phi^2)$ And that the first-order covariance is: ...
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35 views

Why is an ARMA model a parsimonous approximation of an AR model?

I am reading a book on time series and I came across the following: "In addition to being a parsimonous approximation to a high-order AR(p) model, ARMA models...". Why is an ARMA model a (parsimonous) ...
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50 views

When forecasting sequential data is it best to use auto-regressive models or build a more traditional n x p dataset with features?

I'm familiar with the use of auto-regressive models when it comes to forecasting a single vector of time-series data. Is anybody familiar with a more traditional modeling approach, i.e. - creating ...
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1answer
26 views

Estimating auto-correlation with unequally spaced data

I'm working on a time series problem where the spacing between observations is usually 12 or 24 hours, but this is not guaranteed. I'd really like to estimate the auto-correlation function, and I've ...
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1answer
21 views

How to determine if two time series are significantly related to each other

Based on our knowledge of other characteristics of these two variables, we have reason to believe that changes in admits to a ward has an impact on a certain bad outcome on that ward (these are counts ...
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1answer
52 views

find the point at which the curve significantly shoots up

so this is getting a little complex for me and hope someone can help me out. I do not have a mathematical background. I have a time series of daily rainfall for 50 years for a particular location. ...
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1answer
58 views

Time Series Forecasting vs Linear Regression Extrapolation

I'm working on some problems involving prediction of future values. I need to get an aggregated total at some point in the future. My question is: what is the best way to predict the future values? ...
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1answer
92 views

relationship between ARMA and AR

I once heard some statements regarding the relationship between ARMA and AR process, such as An average of severl lags of an autoregression forms an ARMA process ...
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3answers
184 views

stochastic vs deterministic trend/seasonality in time series forecasting

I have moderate background in time series forecasting. I have looked at several forecasting books, and I don't see the following questions addressed in any of them. I have two questions: How would ...
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22 views

Spatial and temporal effects in water quality data

The data I have is 20 sampling points in a water distribution network that have been sampled weekly during 4 months for different parameters (chlorine, turbidity, disinfection by-products, ...). Some ...
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16 views

Predicting one time series from another if they are related - algorithm in R

I am new to time series analysis; I am not even sure if this is even a TS problem. I have looked at other TS posts, but I have a hard time to translate the responses to my needs. For now I am hoping ...
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1answer
32 views

Predicting time series with OpenBUGS

I have a number of fairly short time series (about 4–100 observations) which I need to forecast into the future. I decided to use Bayesian inference, because there is external information about each ...
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32 views

R intercept in arima with xreg

I am trying to understand what the reported intercept is showing when I use arima() with xreg=. The documentation says "If am ...
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21 views

Repeated measures design with measurements from different groups of animals

In a repeated measured design we measure a particular variable at different time points from the same subjects. In animal experiments, if animals are sacrificed at every time point to measure a ...
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1answer
43 views

statistical analysis of events in a given time interval

I am attempting to analyze biological data, to see whether the number of events in a given time interval is more/less than expected based on the overall frequency. How would one approach this? An ...
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12 views

Time series pattern identification - SVD/SSA?

I've looked over other posts regarding time series data, and am unsure if the mentioned methods would apply to what I'm trying to do, since I'm not familiar with pattern analysis methods: I have time ...
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21 views

Is ARIMA(1,0,0)+xreg for level shift the same as linear regression model with level shift adjustment and lag1 term?

I have a time series with a level shift. Thus, when treating it with an ARIMA model, I use arima(1,0,0)+xreg. The xreg is a ...
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1answer
27 views

Test statistic distribution in a cointegrating regression

Let's assume I have a simple cointegrating regression of the type $$y_t=\beta_0+\beta_1x_t+\varepsilon_t$$ $y,x$ are $I(1)$. If testing the OLS residuals I find that $y$ and $x$ are cointegrated, ...
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27 views

“Average” line over irregular log series data

I have simulation data from 1000 runs, plotting some measurable (in this case convergence of the algorithm) as a function of simulation time. Each run produces a discrete set of points ...
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41 views

Computing a distance matrix between multiple multivariate time series

This question has also been asked on stackoverflow.com. Yet my aim is to ask for efficiency gains on the aforementioned platform. My aim here is the correctness of my approach. I am trying to cluster ...
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34 views

SUTSE DLM on daily mean water & air temperature TS

I have two time series: (1) daily mean water temperature from 1988 to 2014 and (2) daily mean air temperature from 1968 to 2010. The water temperature time series has missing data, occurring on ...
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12 views

Seasonal Arima Model

I will appreciate if someone can write the mathematic equation for ARIMA (0,1,0)(2,0,0) 12. I don't need backshift operator in the equation please. I will also appreciate if someone can write the acf ...
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1answer
28 views

spatial-location/time-series prediction models

How efficient it is to build predictive model. However, every crime is dependent on three factors: Time, Spatial Location and people behavior. Statistically, we can't measure people behavior (we ...
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38 views

how do you do regression analysis on advertising impact

i have data that includes clicks, spend, signups and date. for 1 week, i turn off advertising spend to see what clicks and signups are. the next week, i turn advertising back on to see what the new ...
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Assessing Cannibalization, intervention of new mobile app on monthly sales

I am a beginner in statistics and looking for suggestions from you all on the approach for one of my study. For my study, there is a company which sells products via its online website (lets call it ...
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24 views

Question about Time 1/Time 2 analysis

I was hoping to get some input on the best way to test some data that I have collected (using SPSS). In short, respondents make an evaluation at time 1, then complete a distractor task, and then ...
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23 views

How can i perform Cosinor analysis in Matlab?

I have monthly and daily data from births in Greece and i want to to do a cosinor analysis to find the rhythm, (circadian,circannual,half yearly etc etc ) How can i use Matlab to perform the cosinor ...
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25 views

Verification of assumptions in TBATS model

I have a question about using BATS/TBATS models implemented in the forecast package for R. In De Liv­era, Hyndman & Snyder (2011) the models are used without any following analysis. Is it OK to ...
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1answer
70 views

Finding significant peaks — evaluation of different methods

I have a small doubt. My real data looks like this Y values are random values of integers from 0 to 2000. X values run like 1,2,3,4,5,.. to 2 million. Now, my task is to identify significant peaks ...
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1answer
29 views

Individual slopes for many zip codes over time

I have a dataset where I am interested in calculating a slope for each observation / row. I have dependent variable $Y$ that is continuous. Every $Y$ is unique to a zipcode. and my independent / ...
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2answers
41 views

Estimation of so called HAR model

Consider an observed time series $\{Y_t\}_{t=1}^T$ and averaged values $$ Y_t^{(h)}=\frac{1}{h} \sum_{i=0}^{h-1} Y_{t-i} $$ and what is called an HAR model (this is a specific example) $$ ...
2
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1answer
94 views

What is the problem with using R-squared in time series models?

I have read that using R-squared for time series is not appropriate because in a time series context (I know that there are other contexts) R-squared is no longer unique. Why is this? I tried to look ...
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1answer
33 views

Can GARCH be only be used to model a return series?

That is, can I use GARCH or ARCH to model something like sales, gas consumption, data consumption etc or is GARCH/ARCH only for financial applications (i.e. return series)?
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33 views

Granger causality test

How best can I use the Granger causality test in time series data and understand it better because I have never used it. I want to analyze long run relationship and bi-directional relationship between ...
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15 views

Have several low order time series. How do I generate the best prediction?

I have a bunch of data in times series format, December 2013 through March 2014. I have this data for many different factors. Is there a way to take into account all 15000 or so observations in ...
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1answer
66 views

How to interpret autocorrelation

I have calculated autocorrelation on time series data on the patterns of movement of a fish based on its positions: X (x.ts) and Y (...
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14 views

How to handle cut-off weeks in time series analysis?

I am doing a time series analysis of sales data from a data warehouse. For that I want to use data grouped by the week of year. My problem now is that e.g. for week 1/2014, I have an outlier as this ...
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59 views

How to test the ARIMA coefficients?

Which test is required to test whether coefficients estimated as part of ARIMA procedure is different from 0? And how does one compute this test? I am reading some procedures regarding the inversion ...
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1answer
31 views

How can I use the results of GARCH in order to improve a forecast?

I am kind of confused with what I should actually do with predicted volatility values that I obtained via a ARCH/GARCH model other than feeling happy that I know when volatility rises/falls. Is there ...
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60 views

Please help me understand white noise and MA(q) [closed]

I am reading the section about moving average models in Hyndman & Athanasopoulos Forecasting: principles and practice. I am trying to understand the MA(q) model in words. What is white noise? Is ...